• @Valmond@lemmy.world
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    24 days ago

    Ya, it’s like machine learning but better. That’s about it IMO.

    Edit: As I have to spell it out: as opposed to (machine learning with) neural networks.

      • @sugar_in_your_tea@sh.itjust.works
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        824 days ago

        It’s also neural networks, and probably some other CS structures.

        AI is a category, and even specific implementations tend to use multiple techniques.

        • @brucethemoose@lemmy.world
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          424 days ago

          Well there is a very specific architecture “rut” the LLMs people use have fallen into, and even small attempts to break out (like with Jamba) don’t seem to get much interest, unfortunately.

          • @sugar_in_your_tea@sh.itjust.works
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            724 days ago

            Sure, but LLMs aren’t the only AI being used, nor will they eliminate the other forms of AI. As people see issues with the big LLMs, development focus will change to adopt other approaches.

            • @commandar@lemmy.world
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              24 days ago

              There is real risk that the hype cycle around LLMs will smother other research in the cradle when the bubble pops.

              The hyperscalers are dumping tens of billions of dollars into infrastructure investment every single quarter right now on the promise of LLMs. If LLMs don’t turn into something with a tangible ROI, the term AI will become every bit as radioactive to investors in the future as it is lucrative right now.

              Viable paths of research will become much harder to fund if investors get burned because the business model they’re funding right now doesn’t solidify beyond “trust us bro.”

              • @brucethemoose@lemmy.world
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                24 days ago

                the term AI will become every bit as radioactive to investors in the future as it is lucrative right now.

                Well you say that, but somehow crypto is still around despite most schemes being (IMO) a much more explicit scam. We have politicans supporting it.

              • @sugar_in_your_tea@sh.itjust.works
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                224 days ago

                Sure, but those are largely the big tech companies you’re talking about, and research tends to come from universities and private orgs. That funding hasn’t stopped, it just doesn’t get the headlines like massive investments into LLMs currently do. The market goes in cycles, and once it finds something new and promising, it’ll dump money into it until the next hot thing comes along.

                There will be massive market consequences if AI fails to deliver on its promises (and I think it will, because the promises are ridiculous), and we get those every so often. If we look back about 25 years, we saw the same thing w/ the dotcom craze, where anything with a website got obscene amounts of funding, even if they didn’t have a viable business model, and we had a massive crash. But important websites survived that bubble bursting, and the market recovered pretty quickly and within a decade we had yet another massive market correction due to another bubble (the housing market, mostly due to corruption in the financial sector).

                That’s how the market goes. I think AI will crash, and I think it’ll likely crash in the next 5 years or so, but the underlying technologies will absolutely be a core part of our day-to-day life in the same way the Internet is after the dotcom burst. It’ll also look quite a bit different IMO than what we’re seeing today, and within 10 years of that crash, we’ll likely be beyond where we were just before the crash, at least in terms of overall market capitalization.

                It’s a messy cycle, but it seems to work pretty well in aggregate.

                • @commandar@lemmy.world
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                  424 days ago

                  Sure, but those are largely the big tech companies you’re talking about, and research tends to come from universities and private orgs.

                  Well, that’s because the hyperscalers are the only ones who can afford it at this point. Altman has said ChatGPT 4 training cost in the neighborhood of $100M (largely subsidized by Microsoft). The scale of capital being set on fire in the pursuit of LLMs is just staggering. That’s why I think the failure of LLMs will have serious knock-on effects with AI research generally.

                  To be clear: I don’t disagree with you re: the fact that AI research will continue and will eventually recover. I just think that if the LLM bubble pops, it’s going to set things back for years because it will be much more difficult for researchers to get funded for a long time going forward. It won’t be “LLMs fail and everyone else continues on as normal,” it’s going to be “LLMs fail and have significant collateral damage on the research community.”

                  • @sugar_in_your_tea@sh.itjust.works
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                    324 days ago

                    The scale of capital being set on fire in the pursuit of LLMs is just staggering.

                    I’m guessing you weren’t around in the 90s then? Because the amount of money set on fire on stupid dotcom startups was also staggering. Yet here we are, the winners survived and the market is completely recovered now (took about 15 years because 2008 happened).

                    I just think that if the LLM bubble pops, it’s going to set things back for years because it will be much more difficult for researchers to get funded for a long time going forward

                    Maybe. Or if the research is promising enough, investors will dump money into it just like they did with LLMs, and we’ll be right back where we are now with ridiculous valuations.

      • @merc@sh.itjust.works
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        123 days ago

        It is. It’s that plus an important process for living organisms rather than just burning something.